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SYLLABUS — Statistics GR5221/GU4221, Fall 2024
COURSE TITLE: Time Series Analysis
COURSE NUMBER: STAT GR5221/GU4221 (Section 001)
PREREQUISITE(S): STAT GR5205/GU4205 (Linear Regression Models) or the equivalent
TIME & PLACE: Tuesdays and Thursdays, 2:40pm-3:55pm, 312 Mathematics Building
COURSE DESCRIPTION:
This course provides students with modern methods of time series analysis.Topics to be covered include linear process, stationarity, autocorrelation function, ARMA model, Box- Jenkins modeling and forecasting, spectral density and linear filtering, nonstationary time series, and seasonal time series. Examples are from physical sciences, social sciences, business, and other fields of interest. Computing is an integral part of the course.
The course requires a working knowledge of probability, linear algebra, and calculus. You are expected to be able to manipulate random variable expressions and to compute the expected value and variance. Some experience with statistical software is also desired.
REQUIRED TEXT:
Introduction to Time Series and Forecasting, 3rd edition, by Peter J. Brockwell and Richard A. Davis, Springer, 2016, ISBN: 9783319298528.
You may download a FREE .pdf version of the textbook via the CU libraries with your CU credential.
OTHER REFERENCES:
Time Series: Theory and Methods, 2nd edition, by Peter J. Brockwell and Richard A. Davis, Springer, 1991, ISBN: 9781441903198.
Time Series Analysis and its Applications With R Examples, 4th edition, by Robert H. Shumway and David S. Stoffer, Springer, 2017, ISBN: 9783319524511.
Time Series Analysis with Applications in R, 2nd edition, by Jonathan D. Cryer and Kung-Sik Chan, Springer, 2008, ISBN: 9780387759586.
SOFTWARE:
Statistical software package R will be used for data analyses. It can be downloaded for free from The Comprehensive R Archive Network: http://cran.r-project.org/.
The R package 'itsmr' includes some data sets and functions used in the textbook.
On the other hand, you may use the package ITSM2000 that accompanies the textbook for homework questions. Appendix E (An ITSM Tutorial) contains a detailed introduction to the package.
COURSE WEBPAGE:
Syllabus, assignments, and other relevant information/materials will be available via CourseWorks/Canvas. If you have questions about things such as course policies or exam dates, check the course webpage on CourseWorks/Canvas. You are highly recommended to check the course webpage regularly.
There may be adjustments in the scheduling of assignments, exams, and classrooms. Changes will be posted on CourseWorks/Canvas along with other announcements.
GRADING POLICY:
The course grade will be determined in the following manner:
Homework assignments 35%
Project 15%
Midterm 20%
Final 30%
Total 100%
The LETTER GRADE will be assigned according to the following scale:
|
Percentage |
Letter Grade |
|
98% or above |
A+ |
|
93% up to 98% |
A |
|
90% up to 93% |
A- |
|
87% up to 90% |
B+ |
|
83% up to 87% |
B |
|
80% up to 83% |
B- |
|
75% up to 80% |
C+ |
|
70% up to 75% |
C |
|
60% up to 70% |
C- |
|
Under 60% |
F |
*** Note: I do NOT round up! An 89.99% is a B+ not an A-.
In some cases, I may curve the course grades up (but won’t curve downwards); if so, GR5221 and GU4221 will be curved respectively. In general, though not always, the grade distribution will be:
Up to 45% A- and higher
Up to 90% B and higher
If you end up with a course percentage less than 60% and you do not want your course grade to be curved so that you can receive an F to retake the course, you must notify me in advance; otherwise, no change will be made once I have submitted the grades on SSOL.
NOTES REGARDING COURSEWORK:
1. Readings: It is highly recommended that you read the relevant chapters and sections (see Course Schedule on the last page) before each lecture. You are expected to come to class prepared.
2. Assignments: Homework assignments are given for the purpose of helping you understand concepts and calculations. These assignments, posted on the course webpage, are exercises from the textbook. You are required to work on the problems independently, although discussions are encouraged in broad, conceptual terms. The assignments are equally weighted; the one with the lowest score will be dropped. The due date of each assignment will be announced on CourseWorks/Canvas and/or in class.
Your solution should include appropriate explanation and derivation; full credit will not be given to solutions without proper demonstration.
A late assignment within one week after the due date will be penalized as follows: 10% of the grade will be deducted for each additional day after the due date.
o An assignment submitted more than one week after the due date will NOT be accepted.
o For the very last assignment, a late submission will NOT be accepted.
3. Project: A team project, which consists of multiple exercises, asks each team to investigate topics/ questions that extend the class discussions.
The project will be due near the end of the semester.
A late submission within 3 days after the due date will be penalized as follows: 10% of the grade will be deducted for each additional day after the due date.
o A project submitted more than 3 days after the due date will NOT be accepted.
4. Exams: One midterm exam and one final exam will be given. Should you become ill on an exam day, you need to contact me and arrange a makeup exam ASAP. The following policy applies unless you show a valid documented excuse: you will receive
50% of points if taken within one week after the exam date
0% of points if taken more than one week after the exam date
If you do not take the final exam, you will be assigned an “F” grade.